A control system based on prosthetic slip perception and spontaneous grasping

Abstract

The application discloses a control system based on prosthesis slip perception and spontaneous gripping, which comprises a multi-modal integrated sensor module, a digital signal processing module, a peripheral electric stimulation loop module, a prosthesis hand module and an amputee residual limb end module, wherein the prosthesis hand module is installed on the residual limb end of a human body, the multi-modal integrated sensor module is arranged on a mechanical finger of the prosthesis hand module, the multi-modal integrated sensor module collects signals perceived by the prosthesis hand module from the outside world, the digital signal processing module receives and processes the signals collected by the multi-modal integrated sensor module, and the digital signal processing module respectively outputs a waveform of a slip signal to the peripheral electric stimulation loop module and outputs a slip control signal calculated by a reflection loop to the prosthesis hand module. The application realizes rapid and accurate prosthesis hand slip perception and spontaneous gripping control with a physiological nerve reflection mechanism, and can avoid excessive force to crush objects or gripping fatigue.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of prosthetic hand sensory feedback and control, and particularly relates to a control system based on prosthetic hand slip perception and spontaneous grasping. BACKGROUND

[0002] When a healthy person grasps an object with an unknown weight, he can quickly adjust the grasping force according to the load force of the object through the skin and spinal reflex loop, so as to avoid the object from falling due to too small grasping force or being crushed due to too large grasping force. After the slip occurs, the normal person will adjust the grasping force through three stages of short spinal reflex, long spinal reflex and autonomous movement, and the time length from long spinal reflex to autonomous movement of the human body to execute the movement intention is 50-100 milliseconds, and the time length of short spinal reflex is only 20 milliseconds. For amputees, due to the loss of fingers, skin, nerves and the like caused by amputation, it is difficult to adjust the grasping force of the prosthetic hand, not to mention to produce a quick reflex within 100 milliseconds to avoid object slip like a normal person.

[0003] In the existing technologies related to the prevention of slip or the adjustment of grasping of the prosthetic hand, some technologies use distributed pressure sensors, touch and slip sensors, acceleration sensors, angular velocity sensors and infrared temperature sensors respectively placed in the prosthetic fingers, wrists and palms, predict the grasping force of the current grasping action through the improved Takagi-Sugeuo-Kang (TSK) fuzzy recursive cerebellar model and the effective feature information in the electromyographic signal, and feed back the temperature information and contact force information to the user of the prosthetic hand through a vibration unit or a display screen to adjust the grasping force. Some technologies provide a prosthetic hand which is worn on the end of the residual limb of the user through a prosthetic socket, realizes the perception of the approach sensation of the prosthetic hand to the object to be grasped by using a wearable camera module fixed on the chest, realizes the perception of the user to the approach sensation, temperature sensation and force touch sensation of the prosthetic hand by using the wearable force touch feedback devices on the inner side of the palm and fingers and the fingertips, realizes the feedback of the recognition result of the environmental object through the voice interaction module, and prompts the information of completing approach, temperature being too high and grasping the object, etc. The user controls the electromyography according to the guidance to autonomously grasp the object in the environment. Some other technologies use electromyography, near-infrared spectroscopy, muscle sound or a combination of the three sensors, collect biological signals corresponding to the muscle activity of the residual limb, decode the signals through an electrical stimulator or a vibration stimulator, stimulate the residual limb to produce touch, pressure and slip sensations, wear the sensors and stimulators on the residual limb through a telescopic structure, send the movement instructions to the prosthetic control module according to the actions identified by the electromyography to sequentially execute the set training actions, and the patient follows the prosthetic hand to perform the corresponding muscle contraction.

[0004] The existing technologies usually place different functional sensors at the fingertips or different positions of the prosthetic hand, although multi-modal information is obtained, the sensing positions are different, and the sensor layout space position is not enough in the limited space of the prosthetic hand. If the signal collection is not at the same site, there may be deviation of different signal sources, and the complete feedback depends on the use of all hand positions. The information provided by the prosthetic perception feedback mode is mostly based on vibration, sound, electric stimulation, vision and other ways to feedback to the amputee, which is the brain receiving relevant information and then generating a control method. The above feedback methods take too long and cannot make the amputee realize the normal subconscious spontaneous slip perception or adjust the grip. Most of the prosthetic control methods only rely on the electromyography of the amputee, which identifies the action through electromyography and then controls it, or the amputee judges and controls by himself after perceiving the feedback. Electromyography cannot identify the trend of object slip, and the amputee cannot realize slip control in a very short time through electromyography, so as to slip, break the object and cause harm or rejection to the amputee. In addition, the existing prosthetic grip only relies on the visual observation of the amputee to grip the object, and each action needs to be judged and controlled by the amputee. The user is more likely to feel tired and give up the grip of fine objects, which leads to the amputee's reduced willingness to use the prosthetic hand. The existing control model is mostly a threshold, fuzzy and adaptive control model, which cannot reflect the rapid short spinal reflex loop characteristics required by the human hand. Simple threshold control cannot reflect the real control consciousness of the biological body, and lacks the short spinal reflex mechanism of self-motion instructions that can be inhibited or interacted.

[0005] Therefore, the person skilled in the art is committed to providing a control system based on prosthetic slip perception and spontaneous grip, which optimizes the integrated structure of multi-modal sensors to avoid signal source deviation, loss and other problems caused by different sensing positions, and establishes a real bionic neurophysiological reflex mechanism to solve the problem that the amputee cannot quickly perceive and control slip and adjust grip. SUMMARY

[0006] In view of the defects of the prior art, the technical problem to be solved by the present application is how to provide a control system that can quickly perceive and control slip and adjust grip for amputees.

[0007] The application provides a control system based on prosthesis slip perception and spontaneous grasping, which comprises a multi-modal integrated sensor module, a digital signal processing module, a peripheral electric stimulation loop module, a prosthesis hand module, and an amputee residual limb end module, the prosthesis hand module has no less than two mechanical fingers, the prosthesis hand module is installed at the residual limb end of a human body, the multi-modal integrated sensor module is arranged on the mechanical fingers of the prosthesis hand module, the multi-modal integrated sensor module collects signals of the prosthesis hand module, the digital signal processing module receives and processes the signals collected by the multi-modal integrated sensor module, the digital signal processing module respectively outputs a waveform to the peripheral electric stimulation loop module and outputs a slip control signal to the prosthesis hand module, the peripheral electric stimulation loop module outputs transcutaneous electric stimulation of a slip signal, and the amputee residual limb end module can collect electromyographic information and deliver a slip control signal to the prosthesis hand module.

[0008] A commercial prosthesis hand can be connected to the control system, and after collecting electromyographic signals and performing speed, proportional control or threshold, fuzzy and adaptive control on the electromyographic signals, the control system outputs a control signal to drive a joint or the prosthesis hand to perform slip compensation and grasping force adjustment.

[0009] Further, one of the mechanical fingers is controlled by two motors on the prosthesis hand module.

[0010] In the above scheme, a plurality of mechanical fingers or mechanical joints can be simultaneously controlled by two motors.

[0011] Further, the output of the motor is based on a Hill Type muscle model architecture, and the motor controls the movement of the mechanical finger through a wire.

[0012] In the above scheme, the motor can also control the movement of the mechanical finger or the mechanical joint through a screw rod.

[0013] Further, the multi-modal integrated sensor module comprises a slip sensor, a pressure sensor and a temperature sensor, the pressure sensor is arranged on a bottom layer, the temperature sensor is arranged on a top layer, and the slip sensor is arranged between the pressure sensor and the temperature sensor.

[0014] In the above scheme, the temperature sensor can be arranged in an inner ring of the top layer, and the slip sensor can be arranged in an outer ring of the top layer.

[0015] Preferably, the pressure sensor and the slip sensor are made of a capacitive structure of a ball-shaped or ring-shaped corpuscle similar to a human fingertip corpuscle, and the temperature sensor is a thermistor sensor.

[0016] Further, the digital signal processing module uses the bionic intermediate neuron and motor neuron model under the Izhikevich model to calculate the slip control signal.

[0017] Further, the digital signal processing module generates different pulse width stimulation parameters according to the mapping relationship of the peripheral evoked finger sensation and the pressure sensor, the slip sensor and the temperature sensor, and outputs the waveform of the slip signal to the peripheral electrical stimulation loop module.

[0018] Further, the peripheral electrical stimulation loop module includes a plurality of stimulation sub-modules, and the stimulation sub-modules respectively apply electrical stimulation corresponding to the slip sensor, the pressure sensor and the temperature sensor, and the electrical stimulation is applied to the corresponding finger position of the induced finger sensation area or the alternative sensation position of the non-evoked finger sensation area on the end of the residual limb.

[0019] Preferably, the corresponding sensory modalities of the pressure sensor include tapping, pressing, buzzing and vibration, the corresponding sensory modalities of the slip sensor include numbness, and the corresponding sensory modalities of the temperature sensor include needle pricking.

[0020] Preferably, the end of the residual limb module includes an induced finger sensation area and an electromyographic acquisition area.

[0021] The present application has at least the following beneficial technical effects:

[0022] 1. The control system based on prosthesis slip perception and spontaneous gripping provided by the present application improves the sensor structure according to the functional characteristics of the slip, temperature and pressure sensors and the contact range during use by the amputee, proposes a three-layer integrated sensor of pressure-slip-temperature, can simultaneously feedback multi-modal information, improves the efficiency of perception and sensor integration, greatly reduces the space required for sensor arrangement, and improves the consistency of various signal sources, solves the problems of insufficient installation space and inconsistent information of the prosthesis hand sensor.

[0023] 2. The control system based on prosthesis slip perception and spontaneous gripping provided by the present application establishes two kinds of neural circuit mechanisms of slip reflex loop and peripheral electrical stimulation loop, the slip reflex loop corresponds to the short spinal cord reflex of normal people, can provide spontaneous gripping correction compensation under the feedback of slip sensation to the prosthesis controlled by the amputee in a very short time, the peripheral electrical stimulation loop corresponds to the long spinal cord reflex and autonomous movement of normal people, can provide stable and continuous gripping force feedback to the amputee during the process of gripping objects, solves the problems of information feedback and prosthesis hand control gripping not in time and not having biological true characteristics, and the two kinds of neural circuit mechanisms realize rapid and accurate prosthesis hand slip perception and spontaneous gripping control.

[0024] 3. The control system based on prosthesis slip perception and spontaneous gripping provided by the application, the slip reflex loop corresponds to the short spinal cord reflex of normal people, can control the subconscious spontaneous protective measures of the prosthesis hand in a very short time, prevent objects from falling, solve the problem that the prosthesis cannot avoid the object from sliding down due to insufficient force in a very short time; the peripheral electric stimulation loop corresponds to the long spinal cord reflex and autonomous movement of normal people, adjusts through the intermediate neurons possessed in the neuron model, can continue to adjust the gripping force according to the feedback on the basis of ensuring that the object does not fall, and control the prosthesis hand to avoid crushing the object or gripping fatigue due to excessive force.

[0025] The concept, specific structure and technical effects of the application will be further described below in combination with the drawings, so as to fully understand the purpose, features and effects of the application. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 is a schematic diagram of the control system based on prosthesis slip perception and spontaneous gripping provided by the embodiment of the application;

[0027] Figure 2 is a signal processing flowchart of the control system based on prosthesis slip perception and spontaneous gripping provided by the embodiment of the application. DETAILED DESCRIPTION

[0028] The technical content of the application will be clearer and more convenient to understand by introducing a plurality of preferred embodiments of the application with reference to the drawings of the specification. The application can be embodied in many different forms of embodiments, and the protection scope of the application is not limited to the embodiments mentioned in the text.

[0029] In the drawings, the same numbers are used to represent the same components throughout the drawings, and components with similar structures or functions are represented by similar numbers. The size and thickness of each component shown in the drawings are arbitrarily shown, and the size and thickness of each component are not limited in the application. In order to make the drawing clearer, the thickness of some components is appropriately exaggerated in some places in the drawing.

[0030] The application provides a control system based on prosthesis slip perception and spontaneous gripping, which obtains motion information of different positions of the prosthesis hand of an amputee based on a temperature sensor, a slip sensor and a pressure sensor, and then feeds back to the amputee in the form of natural induced finger sensation transcutaneous electric stimulation or non-body substitute sensation transcutaneous electric stimulation for autonomous control. By optimizing the integrated structure of the multi-modal sensor, the problems of signal source deviation and loss caused by different sensing positions are avoided, and by establishing two kinds of neural circuit mechanisms, the problems that the amputee cannot quickly perceive and control the slip and adjust the gripping are solved.

[0031] The control system based on prosthetic slip perception and spontaneous grasping provided in this embodiment includes a multimodal integrated sensor module, a digital signal processing module, a peripheral electrical stimulation circuit module, a prosthetic hand module, and an amputee residual limb end module. The prosthetic hand module imitates a human hand and has no less than two mechanical fingers, usually five. The prosthetic hand module is installed at the residual limb end of the human body. The multimodal integrated sensor module is set on the mechanical fingers of the prosthetic hand module. The multimodal integrated sensor module collects signals from the prosthetic hand module. The digital signal processing module receives and processes the signals collected by the multimodal integrated sensor module. The digital signal processing module outputs the waveform of the slip signal to the peripheral electrical stimulation circuit module and the slip control signal to the prosthetic hand module respectively. The peripheral stimulation circuit module outputs electrical stimulation through the amputee's induced sensing area. The residual limb end can collect electromyographic information in the electromyographic acquisition area, can receive electrical stimulation of the slip signal in the induced finger sensing area, and transmits the slip control signal to the prosthetic hand module.

[0032] The multimodal integrated sensor module includes a pressure sensor, a slip sensor, and a temperature sensor, wherein the pressure sensor is an example of a prosthetic grasping state sensor, the slip sensor is an example of a prosthetic slip state sensor, and the temperature sensor is an example of a prosthetic high temperature warning state. The pressure sensor and the slip sensor are made of a special capacitive structure that simulates the Ruffini corpuscles (spherical or ring-shaped corpuscles) of the fingertips. The pressure sensor and the slip sensor cause the capacitive structure to change as they move in the vertical and shear directions of the contact object, thereby being able to sense pressure and slip based on the partial pressure information. The temperature sensor is made of a thermistor and produces different Bezier curves after contacting different temperatures. It should be understood that other types of sensors can also be used as gripping state and slip state sensors, such as displacement sensors, contact sensors, and other sensors or bionic skins that include a combination of types such as slip and pressure sensors.

[0033] like Figure 1 As shown, the pressure sensor is located on the bottom layer, the slip sensor is in the middle, and the temperature sensor is placed on the top layer. When the prosthetic limb touches an object, the integrated sensor on the fingertip converts digital-to-analog signals and amplifies them through voltage division, sending three digital signals to the digital signal processing module. In this embodiment, the multimodal integrated sensor can be placed in various locations, such as the fingertip, fingertips, and palm.

[0034] In other embodiments, the temperature sensor may be placed on the inner ring of the top layer, and the slip sensor may be placed on the outer ring of the top layer.

[0035] In addition to integrating three functions, the multimodal integrated sensor of this embodiment also optimizes the layout of each sensor on the prosthesis. This setting can improve perception and sensing efficiency and does not rely on the use of all hand positions.

[0036] The digital signal processing module includes a microprocessor and its carried slip reflection loop and electric stimulation waveform output, and is further divided into digital-analog converter, sensor signal processing, evoked finger sensation coding, intermediate neuron, motor neuron, muscle model and other functional units, as shown in Figure 2 The input of the digital signal processing module is received through the physical connection line, using SPI, I2C, GPIO, serial port or USB connection mode, to receive the digital signal transmitted by the multi-modal integrated sensor, or through the A / D acquisition module in the digital signal processing module to receive the analog signal of the multi-modal integrated sensor. The connection between the digital signal module and the prosthetic hand module and the peripheral electric stimulation loop module is in the form of SPI, I2C, GPIO, serial port or USB. It should be understood that the processing mode of the digital signal processing module is not limited to a microprocessor, but can also be other programmable data processors that process computer readable program instructions, and the communication mode of the digital module is not limited to the above connection mode, but can also be other communication modes that meet the computer instructions.

[0037] The digital-to-analog converter converts the received three sensor analog signals into voltage signals, and calculates the corresponding pressure, slip, and temperature information through sensor signal processing such as filtering and sliding window. The slip signal is first calculated by the slip reflex loop (intermediate neurons and motor neurons), and then the slip information is pulse width coded, and the pressure information is directly pulse width coded. The intermediate neurons and motor neurons based on the Izhikevich neuron model form the slip reflex loop, and the Izhikevich model can represent the process of generating local potential, threshold potential, peak potential (pulse), depolarization potential, and hyperpolarization potential after receiving synaptic current, and forming excitatory or inhibitory activity. When there is no slip information, the loop has no output, and when there is slip information, it is simulated as synaptic current into the intermediate neuron, and if the threshold potential is reached, the peak potential is generated, which is considered as the intermediate neuron firing, generating the slip reflex. Subsequently, the pulses enter the extensor and flexor motor neurons, respectively. According to the number of slip reflex pulses, the flexor motor neuron calculates the excitatory motor command, and the extensor motor neuron calculates the inhibitory motor command. The extensor and flexor motor commands are output to the HillType muscle model, and then the motor command is sent to the prosthetic hand module to control the prosthetic flexor to increase and the extensor to decrease in a very short time, forming the action of gripping the object to avoid slipping and restoring the short spinal cord reflex of the amputee. The control loop based on the HillType muscle model represents the force-length characteristics of the two commonly used muscles of the amputee's finger flexor and extensor, which have a nonlinear mechanical property similar to a quadratic parabola, and can meet the requirement of adjusting the gripping force in a small range. It should be understood that the neuron model in the slip reflex loop can also be a Leaky Integrate-and-Fire (LIF), Hodgkin-Huxlex (HH) neuron model or other artificial neural networks, and the method of calculating the motor command based on the slip reflex can be any calculation method that describes the linear relationship between the slip signal input and the neuron pulse output; the muscle model can also be the muscle model proposed by other scholars such as Zajac, Shadmehr, and Brown.

[0038] The slip signal is first calculated by the slip reflex loop, and then the pulse width is encoded according to the slip generated pulse. The pressure information is directly encoded by pulse width. The induced finger sensation encoding is calculated by the size of the pulse generated by the slip and the pressure information according to the previously determined frequency and amplitude. If the slip and pressure information is less than the minimum threshold value, it is encoded as 0. If it is greater than the maximum threshold value, it is encoded as the maximum pulse width. If it is between the minimum pulse width and the maximum pulse width, the pulse width has a corresponding linear relationship with the slip and pressure information. Then, according to the placement position of the multi-modal integrated sensor corresponding to the induced finger sensation area or other alternative area, the pulse width, amplitude, frequency and other parameters are sent to the corresponding sub-stimulation module in the peripheral electric stimulation loop module to determine the different types and intensities of electric stimulation waveform for the amputee. It should be understood that the induced finger sensation encoding can be any other encoding method with a linear relationship with the sensing information.

[0039] According to the induced finger sensation encoding parameters output by the digital signal processing module, different electric stimulations are applied in different induced finger sensation areas. The electric stimulation helps the amputee to produce different types and intensities of sensations through the surface electric stimulation electrode, mainly the real real body finger sensation under the specific induced finger sensation area of the amputee, or the peripheral or brain cortex nerve implantable stimulation or other non-specific area alternative sensation electric stimulation.

[0040] In one specific embodiment, the slip reflex loop uses a biomimetic intermediate neuron and motor neuron model constructed under the Izhikevich model of biological reality, where v represents the neuron membrane potential, and u represents the neuron recovery variable. The units of u and v are millivolts (mV). I is the slip signal after analysis and processing, with a unit of mV, simulating synaptic current. a, b, c, d are unitless parameters that change with the type of neuron. The slip signal is calculated by the biomimetic loop. If the threshold value of the neuron v≥30mV is exceeded, the neuron starts to continuously fire pulses, which is considered to generate slip reflex. The number of pulses N fired by the neuron can reflect the size of the slip signal. The greater N is, the higher the degree of slip is, and the more excited the neuron is. k represents a linear parameter matched with the amplitude of the electromyogram. Then, the slip and grip are adjusted according to the excitatory or inhibitory relationship of the intermediate neuron. This loop can output control extensor movement instruction a_flx and flexor movement instruction a_ext in a very short time, and control the prosthesis to immediately grip the object through the muscle model.

[0041]

[0042]

[0043]

[0044] α flx =k×N

[0045] a ext = -k x N

[0046] After identifying and processing the pressure, slip signals, the electrical stimulation coding produces different pulse width stimulation parameters according to the mapping relationship of the peripheral evoked finger sensation and the pressure, slip, temperature sensors, and outputs different waveforms to the peripheral electrical stimulation loop. Through the identification of different sensory sensitivity, the minimum and maximum electrical stimulation amplitude A and frequency F causing a certain sensation are first determined, and the encoding relationship between the pulse width W and the slip, pressure, temperature sensor input value S is shown in the following figure.

[0047]

[0048] The peripheral electrical stimulation module can form different types and intensities of perceptual feedback output by the peripheral electrical stimulation loop, and the amputee can adjust the myoelectricity size to reflect the movement intention of grasping by himself with the help of feedback, can restore long spinal reflex and autonomous movement, and continue to adjust the grasping force on the basis of the slip reflex loop to prevent crushing objects or grasping fatigue. The peripheral electrical stimulation loop module contains multiple stimulation sub-modules according to the number and position of the finger sensation area, respectively applies electrical stimulation corresponding to slip, pressure, and temperature, and determines six different finger-to-finger substitution sensations of light touch, pressing, humming, vibration, numbness, and needle sticking through the amputee's finger sensation area. Different sensory modes correspond to different strength sensory modalities of the prosthetic hand, of which the first four correspond to the pressure sensory modality, numbness corresponds to the slip sensory modality, and needle sticking corresponds to the temperature sensory modality.

[0049] The mechanical fingers of the prosthetic hand module are established by the extensor and flexor muscle models, and are driven by two motors. The driven prosthetic hand can be an underactuated prosthetic hand, a wire-driven prosthetic hand, or a commercial motor prosthetic hand. The change in the length of the motor pull wire simulates the process of muscle contraction, and the output force of the motor depends on the downlink movement instruction of the digital signal processing module and the myoelectricity size fed back according to the peripheral electrical stimulation loop module. As the prosthetic hand grasps an object, the integrated sensor on the fingertip also acquires real-time pressure, slip, temperature, and other information, which is then sequentially passed through the digital signal processing module and the peripheral electrical stimulation path module to form a sensing-perception-control loop.

[0050] In one specific embodiment, the output of each motor on the mechanical fingers of the prosthetic hand module is based on the Hill Type muscle model architecture. The motor controls the movement of the prosthetic finger through the pull wire, can directly adjust the muscle model according to the downlink movement instruction of the slip reflex loop, and the myoelectricity fed back after the peripheral electrical stimulation loop can also adjust the muscle model. The two neural circuits can simultaneously adjust the muscle model to control the movement of the motor, pull the prosthetic hand to grasp an object, and adjust the grasping force.

[0051] In other embodiments, multiple mechanical fingers or mechanical joints can also be controlled simultaneously by the two motors through the common contraction, and the motors control the movement of the mechanical fingers or mechanical joints through the screw rod.

[0052] The residual limb end module includes a finger induction area and an electromyography collection area. After amputation, the nerves are not completely cut off, and part of the nerve endings are retained. These nerve endings can still perceive different types and intensities of stimulation, providing a physiological basis for determining the finger induction area. The electromyography collection area is located above the residual limb of the amputee. The position of the largest and most obvious muscle during the contraction and relaxation of the amputee's residual limb is selected as the electromyography collection area. The electromyography of the lateral wrist extensor and wrist flexor of the amputee is collected using electromyography electrodes. The motion command is extracted by smoothing the electromyography through Bayesian filtering. The finger induction area is determined by pressing, stimulating, and asking. It should be understood that the finger induction area can also be other alternative areas on the non-amputated end, such as the chest, the opposite finger, the opposite right arm, and other areas that can produce non-evoked finger sensation; the processing of the electromyography signal can also be other filters.

[0053] The residual limb end module is arranged in the finger induction area to receive electrical stimulation and perceive and recognize different types and intensities of feelings of different fingers in this area. The amputee can control the electromyography independently after perceiving the feedback to realize the motion intention through the electromyography collection area. The electrical stimulation can also be applied to the alternative sensation points on the non-evoked finger induction area.

[0054] The above describes the preferred embodiments of the application in detail. It should be understood that those skilled in the art can make many modifications and changes without creative labor based on the concept of the application. Therefore, any technical solution obtained by logical analysis, reasoning or limited experiment based on the existing technology according to the concept of the application should be within the protection scope determined by the claims.

Claims

1. A control system based on prosthetic slip perception and spontaneous grasping, characterized in that: The invention comprises a multimodal integrated sensor module, a digital signal processing module, a peripheral electrical stimulation circuit module, a prosthetic hand module and an amputee residual limb end module, wherein the prosthetic hand module has no less than two mechanical fingers and is installed at the residual limb end of a human body, the multimodal integrated sensor module is arranged on the mechanical fingers of the prosthetic hand module, the multimodal integrated sensor module collects the signal of the prosthetic hand module, the digital signal processing module receives and processes the signal collected by the multimodal integrated sensor module, the digital signal processing module outputs waveforms to the peripheral electrical stimulation circuit module and outputs slip control signals to the prosthetic hand module respectively, the peripheral electrical stimulation circuit module outputs transcutaneous electrical stimulation of the slip signal, the amputee residual limb end module can collect myoelectric information and transmit the slip control signal to the prosthetic hand module; the multimodal integrated sensor module comprises a slip sensor, a pressure sensor and a temperature sensor, the pressure sensor is placed on the bottom layer, the temperature sensor is placed on the top layer, and the slip sensor is placed between the pressure sensor and the temperature sensor; the digital signal processing module uses the bionic intermediate neuron and motor neuron model constructed under the Izhikevich model to calculate the slip control signal; the digital signal processing module generates stimulation parameters with different pulse widths according to the mapping relationship between the peripheral induced finger sensation and the pressure sensor, the slip sensor, and the temperature sensor, and outputs the waveform of the slip signal to the peripheral electrical stimulation circuit module; the peripheral electrical stimulation circuit module includes a plurality of stimulation sub-modules, and the stimulation sub-modules respectively apply electrical stimulation corresponding to the slip sensor, the pressure sensor, and the temperature sensor, and the electrical stimulation is respectively applied to the finger sites corresponding to the induced finger sensation area on the residual limb end or the alternative sensory sites in the non-induced finger sensation area.

2. The control system based on prosthetic slip perception and spontaneous grasping according to claim 1, characterized in that: The prosthetic hand module controls one of the mechanical fingers via two motors.

3. The control system based on prosthetic slippage perception and spontaneous grasping according to claim 2, characterized in that: The output of the motor is based on the HillType muscle model architecture, and the motor controls the movement of the robotic finger through a pull wire.

4. The control system based on prosthetic slip perception and spontaneous grasping according to claim 1, characterized in that: The pressure sensor and the slip sensor are made of capacitive structures of spherical or ring-shaped corpuscles simulating Ruffini corpuscles at the fingertips, and the temperature sensor is a thermistor sensor.

5. The control system based on prosthetic slippage perception and spontaneous grasping according to claim 1, characterized in that: The sensory modalities corresponding to the pressure sensor include light touch, pressing, humming, and vibration; the sensory modalities corresponding to the slip sensor include numbness; and the sensory modalities corresponding to the temperature sensor include a needle prick.

6. The control system based on prosthetic slippage perception and spontaneous grasping according to claim 1, characterized in that: The residual limb end module includes a finger-sensing area and an electromyographic acquisition area.

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